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Tail

index transition_to_stage transition_from_stage_name opportunity_status opportunity_type core_consumption_market core_product_segment core_sales_segment geography core_product_application stage_level transition_time_days decision_time_days early_stages did_convert product_id product_$ product_quantity target
12744 88870.000000 0.970140 0.950087 0.966951 0.499614 0.545786 0.489466 0.499836 0.550499 0.558594 1.000000 5.000000 69.000000 0.646537 0.966951 0.500000 425.000000 25.000000 0
12745 22608.000000 0.057836 0.098784 0.166704 0.499614 0.440150 0.489466 0.499836 0.525655 0.494337 0.250000 0.000000 32.000000 0.234339 0.158535 0.600000 722688.000000 3764.000000 0
12746 69033.000000 0.091408 0.362647 0.166704 0.499614 0.455556 0.489466 0.499836 0.550499 0.558594 0.250000 5.000000 112.000000 0.234339 0.158535 0.500000 14040.000000 120.000000 0
12747 75757.000000 0.057836 0.098784 0.166704 0.499614 0.481184 0.489466 0.499836 0.464878 0.497863 0.250000 0.000000 31.000000 0.234339 0.158535 0.500000 1124.000000 4.000000 0
12748 18485.000000 0.297586 0.362647 0.166704 0.499614 0.374421 0.489466 0.499836 0.464878 0.497863 0.500000 5.000000 13.000000 0.234339 0.158535 0.666667 4500.000000 500.000000 0

Pre Processing

Pre Processing - Imputations

Pre Processing - Imputations - Missing

No missing values in data

Pre Processing - Imputations - Infinitys

No Infinity values

Health Analysis

Health Plot

Missing Plot

Missing Value Summary

No Missing Values

Duplicate Columns

No duplicate variables

Outliers In Features

Data Shape:(12749, 19)
feature < (mean-3*std) > (mean+3*std) < (1stQ - 1.5 * IQR) > (3rdQ + 1.5 * IQR) -inf +inf
opportunity_type 0 0 1361 0 0 0
core_product_segment 328 0 795 0 0 0
core_sales_segment 419 0 1930 1021 0 0
geography 886 0 886 0 0 0
core_product_application 360 0 2230 1227 0 0
stage_level 463 0 463 0 0 0
transition_time_days 0 585 0 1092 0 0
decision_time_days 0 291 0 679 0 0
product_$ 0 283 0 1700 0 0
product_quantity 0 307 0 1780 0 0

Feature Analysis

Summary Stats

Summary Stats - Numeric Variables

Variable Name Datatype No of Unique Samples Mean Standard Deviation Min 25th percentile Median 75th percentile Max
0 core_consumption_market float64 15 [0.3676371022342586, 0.4503901895206243, 0.5457856399583767, 0.4642375168690958, 0.3744207599629286] 0.479246 0.068826 0.344262 0.440150 0.481184 0.545786 0.588721
1 core_product_application float64 13 [0.49786259541984734, 0.4943373733359825, 0.41926477431363424, 0.55859375, 0.564625850340136] 0.482459 0.053112 0.271935 0.494337 0.497863 0.497863 0.564626
2 core_product_segment float64 4 [0.4894655875861146, 0.3287605304156328, 0.4309090909090909, 0.4230769230769231] 0.483174 0.027422 0.328761 0.489466 0.489466 0.489466 0.489466
3 core_sales_segment float64 8 [0.4998362266622994, 0.3516295025728988, 0.5732217573221757, 0.24365741445642355, 0.6183035714285714] 0.481577 0.071304 0.243657 0.499836 0.499836 0.499836 0.618304
4 decision_time_days float64 378 [24.0, 52.0, 15.0, 70.0, 281.0] 81.592880 84.715762 -83.000000 23.000000 57.000000 119.000000 347.799405
5 did_convert float64 2 [0.9669512966476913, 0.15853531675855612] 0.478630 0.395375 0.158535 0.158535 0.158535 0.966951 0.966951
6 early_stages float64 2 [0.6465371621621622, 0.23433874709976799] 0.478961 0.202475 0.234339 0.234339 0.646537 0.646537 0.646537
7 geography float64 5 [0.46487752161383283, 0.550499001996008, 0.2392792359256779, 0.5256550218340611, 0.44449013157894735] 0.479561 0.077983 0.239279 0.464878 0.464878 0.550499 0.550499
8 index float64 12495 [1809.0, 76414.0, 15749.0, 87640.0, 913.48] 54288.817554 30173.812442 913.480000 27466.000000 57247.000000 81950.000000 97693.520000
9 opportunity_status float64 3 [0.9669512966476913, 0.16670356431259686, 0.031088082901554404] 0.478639 0.396161 0.031088 0.166704 0.166704 0.966951 0.966951
10 opportunity_type float64 2 [0.4996138996138996, 0.30851063829787234] 0.479213 0.059015 0.308511 0.499614 0.499614 0.499614 0.499614
11 product_$ float64 2574 [707400.0, 553500.0, 1742.0, 23506.0, 477700.0] 465970.315308 1250161.916009 0.000000 4800.000000 58950.000000 281000.000000 7148082.992446
12 product_id float64 28 [0.6666666666666666, 0.75, 0.5, 0.6, 0.0] 0.478703 0.344624 0.000000 0.000000 0.500000 0.666667 1.000000
13 product_quantity float64 1018 [1800.0, 1500.0, 13.0, 146.0, 1700.0] 11306.413858 40001.535273 1.000000 56.000000 600.000000 2800.000000 226269.114908
14 stage_level float64 6 [1.0, 0.25, 0.5, 0.75, -0.7026916522369855] 0.615178 0.397834 -0.702692 0.250000 0.500000 1.000000 1.000000
15 transition_from_stage_name float64 8 [0.9500870574579222, 0.3626465661641541, 0.5695150115473441, 0.09878419452887538, 0.26920415224913496] 0.479678 0.301501 0.046296 0.200813 0.362647 0.569515 0.950087
16 transition_time_days float64 277 [6.03, 5.0, 0.33, 3.67, 8.33] 4.180154 5.032562 0.000000 0.330000 3.280000 5.000000 20.683234
17 transition_to_stage float64 8 [0.970139565076274, 0.09140767824497258, 0.29758576874205844, 0.03225806451612903, 0.05783582089552239] 0.478756 0.405909 0.030691 0.091408 0.297586 0.970140 0.970140

Summary Stats - Non Numeric Variables

Variable Name Datatype No of Unique Samples Mode Mode Freq Mode Freq %
0 target int32 2 [1, 0] 0 6638 52.066829

Distributions

Distributions - Numeric Variables

Distributions - Numeric Variables - Core Consumption Market

Distributions - Numeric Variables - Core Product Application

Distributions - Numeric Variables - Core Product Segment

Distributions - Numeric Variables - Core Sales Segment

Distributions - Numeric Variables - Decision Time Days

Distributions - Numeric Variables - Did Convert

Distributions - Numeric Variables - Early Stages

Distributions - Numeric Variables - Geography

Distributions - Numeric Variables - Index

Distributions - Numeric Variables - Opportunity Status

Distributions - Numeric Variables - Opportunity Type

Distributions - Numeric Variables - Product $

Distributions - Numeric Variables - Product Id

Distributions - Numeric Variables - Product Quantity

Distributions - Numeric Variables - Stage Level

Distributions - Numeric Variables - Target

Distributions - Numeric Variables - Transition From Stage Name

Distributions - Numeric Variables - Transition Time Days

Distributions - Numeric Variables - Transition To Stage

Distributions - Non Numeric Variables

No categorical variables in data.

Feature Normality

Feature Interactions

Correlation Table

Variable 1 Variable 2 Corr Coef Abs Corr Coef
0 did_convert opportunity_status 0.997998 0.997998
1 opportunity_status transition_to_stage 0.975869 0.975869
2 did_convert transition_to_stage 0.973910 0.973910
3 opportunity_status stage_level 0.814914 0.814914
4 target transition_to_stage 0.811768 0.811768
5 stage_level transition_to_stage 0.811396 0.811396
6 opportunity_status target 0.791209 0.791209
7 did_convert target 0.789561 0.789561
8 did_convert stage_level 0.783179 0.783179
9 transition_from_stage_name transition_to_stage 0.745659 0.745659
10 opportunity_status transition_from_stage_name 0.710441 0.710441
11 did_convert transition_from_stage_name 0.707499 0.707499
12 product_id target 0.688741 0.688741
13 early_stages transition_from_stage_name 0.672151 0.672151
14 stage_level target 0.659033 0.659033
15 core_product_application core_product_segment 0.619538 0.619538
16 target transition_from_stage_name 0.606047 0.606047
17 stage_level transition_from_stage_name 0.597330 0.597330
18 core_sales_segment opportunity_type 0.589794 0.589794
19 product_$ product_quantity 0.581370 0.581370
20 product_id transition_to_stage 0.553720 0.553720
21 opportunity_status product_id 0.516623 0.516623
22 early_stages transition_to_stage 0.510938 0.510938
23 did_convert product_id 0.506939 0.506939
24 product_id stage_level 0.491704 0.491704
25 did_convert early_stages 0.467006 0.467006
26 early_stages opportunity_status 0.456602 0.456602
27 core_sales_segment product_quantity -0.445852 0.445852
28 early_stages stage_level 0.429588 0.429588
29 early_stages target 0.408955 0.408955
30 core_product_segment core_sales_segment 0.399845 0.399845
31 decision_time_days product_id -0.397302 0.397302
32 product_id transition_from_stage_name 0.387020 0.387020
33 core_product_application core_sales_segment 0.385475 0.385475
34 opportunity_type product_quantity -0.350889 0.350889
35 core_consumption_market opportunity_type 0.344676 0.344676
36 core_consumption_market core_sales_segment 0.327860 0.327860
37 core_product_segment product_quantity -0.319781 0.319781
38 core_product_application product_quantity -0.300141 0.300141
39 opportunity_type product_$ -0.297058 0.297058
40 core_sales_segment product_$ -0.295706 0.295706
41 decision_time_days target -0.251079 0.251079
42 decision_time_days transition_to_stage -0.243761 0.243761
43 decision_time_days opportunity_type -0.240996 0.240996
44 core_product_segment opportunity_type 0.240510 0.240510
45 index transition_time_days -0.231463 0.231463
46 geography index 0.229380 0.229380
47 core_sales_segment product_id 0.224400 0.224400
48 early_stages product_id 0.210287 0.210287
49 decision_time_days opportunity_status -0.208601 0.208601
50 decision_time_days did_convert -0.207957 0.207957
51 decision_time_days product_$ 0.206955 0.206955
52 core_consumption_market decision_time_days -0.206934 0.206934
53 core_consumption_market product_id 0.203280 0.203280
54 core_sales_segment decision_time_days -0.201843 0.201843
55 core_product_application opportunity_type 0.198240 0.198240
56 opportunity_type product_id 0.197289 0.197289
57 core_product_application product_id 0.190678 0.190678
58 core_consumption_market product_quantity -0.185904 0.185904
59 decision_time_days stage_level -0.172575 0.172575
60 decision_time_days product_quantity 0.172240 0.172240
61 core_consumption_market product_$ -0.170477 0.170477
62 product_$ product_id -0.161004 0.161004
63 geography target 0.155727 0.155727
64 core_sales_segment target 0.153810 0.153810
65 did_convert geography 0.149225 0.149225
66 core_consumption_market core_product_segment 0.147877 0.147877
67 geography opportunity_status 0.146485 0.146485
68 core_product_application stage_level 0.145667 0.145667
69 decision_time_days transition_from_stage_name -0.144589 0.144589
70 geography transition_to_stage 0.142721 0.142721
71 core_consumption_market core_product_application 0.140262 0.140262
72 core_product_application transition_to_stage 0.137913 0.137913
73 core_product_segment product_id 0.136831 0.136831
74 core_product_application target 0.135586 0.135586
75 core_consumption_market target 0.135521 0.135521
76 core_sales_segment stage_level 0.134532 0.134532
77 early_stages transition_time_days 0.133212 0.133212
78 product_id product_quantity -0.133111 0.133111
79 core_product_application opportunity_status 0.132570 0.132570
80 core_product_segment product_$ -0.130915 0.130915
81 core_product_application did_convert 0.129173 0.129173
82 core_sales_segment transition_to_stage 0.126458 0.126458
83 core_sales_segment opportunity_status 0.125881 0.125881
84 core_product_segment stage_level 0.124133 0.124133
85 core_consumption_market transition_to_stage 0.123949 0.123949
86 core_sales_segment did_convert 0.122644 0.122644
87 decision_time_days index -0.119944 0.119944
88 core_product_application decision_time_days -0.119606 0.119606
89 opportunity_type target 0.114590 0.114590
90 early_stages index -0.112903 0.112903
91 transition_from_stage_name transition_time_days 0.112410 0.112410
92 core_product_application product_$ -0.112118 0.112118
93 core_consumption_market opportunity_status 0.109330 0.109330
94 product_$ target -0.108228 0.108228
95 core_product_segment transition_to_stage 0.108203 0.108203
96 core_consumption_market did_convert 0.108181 0.108181
97 geography transition_from_stage_name 0.107861 0.107861
98 core_consumption_market stage_level 0.107758 0.107758
99 index transition_from_stage_name -0.105148 0.105148
100 core_product_segment opportunity_status 0.104603 0.104603
101 core_product_segment target 0.101402 0.101402
102 core_product_segment did_convert 0.101378 0.101378
103 core_product_application transition_from_stage_name 0.098021 0.098021
104 opportunity_type transition_to_stage 0.096722 0.096722
105 product_$ transition_to_stage -0.096469 0.096469
106 geography stage_level 0.096052 0.096052
107 product_quantity stage_level -0.095851 0.095851
108 geography product_id 0.095402 0.095402
109 opportunity_type stage_level 0.090904 0.090904
110 opportunity_status opportunity_type 0.088319 0.088319
111 product_quantity target -0.088300 0.088300
112 product_quantity transition_to_stage -0.088166 0.088166
113 product_$ stage_level -0.086804 0.086804
114 opportunity_status product_$ -0.085280 0.085280
115 did_convert opportunity_type 0.085123 0.085123
116 did_convert product_$ -0.082705 0.082705
117 core_product_segment decision_time_days -0.081206 0.081206
118 core_product_segment transition_from_stage_name 0.080784 0.080784
119 opportunity_status product_quantity -0.080513 0.080513
120 decision_time_days early_stages -0.079894 0.079894
121 did_convert product_quantity -0.077568 0.077568
122 core_consumption_market transition_from_stage_name 0.077362 0.077362
123 early_stages geography 0.077295 0.077295
124 index opportunity_type -0.071756 0.071756
125 index transition_to_stage -0.067764 0.067764
126 decision_time_days transition_time_days 0.063361 0.063361
127 core_product_segment early_stages 0.059491 0.059491
128 core_sales_segment transition_from_stage_name 0.057247 0.057247
129 core_product_application early_stages 0.056182 0.056182
130 index product_$ -0.056047 0.056047
131 product_$ transition_from_stage_name -0.055455 0.055455
132 index product_quantity -0.055044 0.055044
133 index product_id -0.054350 0.054350
134 core_consumption_market early_stages 0.048310 0.048310
135 product_quantity transition_from_stage_name -0.047293 0.047293
136 did_convert index -0.046376 0.046376
137 core_consumption_market geography 0.044687 0.044687
138 core_product_segment index -0.043647 0.043647
139 core_sales_segment index 0.042764 0.042764
140 index opportunity_status -0.042496 0.042496
141 geography product_$ -0.038172 0.038172
142 product_quantity transition_time_days 0.038031 0.038031
143 core_sales_segment transition_time_days -0.036853 0.036853
144 geography transition_time_days 0.036451 0.036451
145 index target -0.036181 0.036181
146 core_consumption_market transition_time_days -0.034985 0.034985
147 product_$ transition_time_days 0.033915 0.033915
148 opportunity_type transition_from_stage_name 0.033569 0.033569
149 product_id transition_time_days -0.032019 0.032019
150 opportunity_status transition_time_days -0.028531 0.028531
151 did_convert transition_time_days -0.028429 0.028429
152 core_sales_segment geography 0.028005 0.028005
153 geography product_quantity -0.028000 0.028000
154 transition_time_days transition_to_stage -0.027868 0.027868
155 early_stages product_quantity -0.023200 0.023200
156 opportunity_type transition_time_days -0.022459 0.022459
157 core_sales_segment early_stages 0.021472 0.021472
158 stage_level transition_time_days -0.021313 0.021313
159 decision_time_days geography 0.019948 0.019948
160 core_product_segment geography -0.018935 0.018935
161 early_stages product_$ -0.017663 0.017663
162 early_stages opportunity_type -0.017222 0.017222
163 core_product_application geography -0.013646 0.013646
164 target transition_time_days -0.009364 0.009364
165 index stage_level -0.007877 0.007877
166 core_consumption_market index 0.005350 0.005350
167 core_product_segment transition_time_days 0.004032 0.004032
168 core_product_application index -0.002244 0.002244
169 geography opportunity_type 0.001569 0.001569
170 core_product_application transition_time_days 0.000733 0.000733

Correlation Heatmap

Covariance Heatmap

Bivariate Plots (top 50 Correlations)

Bivariate Plots (top 50 Correlations) - Opportunity Status Vs Did Convert

Bivariate Plots (top 50 Correlations) - Transition To Stage Vs Opportunity Status

Bivariate Plots (top 50 Correlations) - Transition To Stage Vs Did Convert

Bivariate Plots (top 50 Correlations) - Stage Level Vs Opportunity Status

Bivariate Plots (top 50 Correlations) - Transition To Stage Vs Target

Bivariate Plots (top 50 Correlations) - Transition To Stage Vs Stage Level

Bivariate Plots (top 50 Correlations) - Target Vs Opportunity Status

Bivariate Plots (top 50 Correlations) - Target Vs Did Convert

Bivariate Plots (top 50 Correlations) - Stage Level Vs Did Convert

Bivariate Plots (top 50 Correlations) - Transition To Stage Vs Transition From Stage Name

Bivariate Plots (top 50 Correlations) - Transition From Stage Name Vs Opportunity Status

Bivariate Plots (top 50 Correlations) - Transition From Stage Name Vs Did Convert

Bivariate Plots (top 50 Correlations) - Target Vs Product Id

Bivariate Plots (top 50 Correlations) - Transition From Stage Name Vs Early Stages

Bivariate Plots (top 50 Correlations) - Target Vs Stage Level

Bivariate Plots (top 50 Correlations) - Core Product Segment Vs Core Product Application

Bivariate Plots (top 50 Correlations) - Transition From Stage Name Vs Target

Bivariate Plots (top 50 Correlations) - Transition From Stage Name Vs Stage Level

Bivariate Plots (top 50 Correlations) - Opportunity Type Vs Core Sales Segment

Bivariate Plots (top 50 Correlations) - Product Quantity Vs Product $

Bivariate Plots (top 50 Correlations) - Transition To Stage Vs Product Id

Bivariate Plots (top 50 Correlations) - Product Id Vs Opportunity Status

Bivariate Plots (top 50 Correlations) - Transition To Stage Vs Early Stages

Bivariate Plots (top 50 Correlations) - Product Id Vs Did Convert

Bivariate Plots (top 50 Correlations) - Stage Level Vs Product Id

Bivariate Plots (top 50 Correlations) - Early Stages Vs Did Convert

Bivariate Plots (top 50 Correlations) - Opportunity Status Vs Early Stages

Bivariate Plots (top 50 Correlations) - Stage Level Vs Early Stages

Bivariate Plots (top 50 Correlations) - Target Vs Early Stages

Bivariate Plots (top 50 Correlations) - Core Sales Segment Vs Core Product Segment

Bivariate Plots (top 50 Correlations) - Transition From Stage Name Vs Product Id

Bivariate Plots (top 50 Correlations) - Core Sales Segment Vs Core Product Application

Bivariate Plots (top 50 Correlations) - Opportunity Type Vs Core Consumption Market

Bivariate Plots (top 50 Correlations) - Core Sales Segment Vs Core Consumption Market

Bivariate Plots (top 50 Correlations) - Opportunity Type Vs Core Product Segment

Bivariate Plots (top 50 Correlations) - Index Vs Geography

Bivariate Plots (top 50 Correlations) - Product Id Vs Core Sales Segment

Bivariate Plots (top 50 Correlations) - Product Id Vs Early Stages

Bivariate Plots (top 50 Correlations) - Product $ Vs Decision Time Days

Bivariate Plots (top 50 Correlations) - Product Id Vs Core Consumption Market

Bivariate Plots (top 50 Correlations) - Opportunity Type Vs Core Product Application

Bivariate Plots (top 50 Correlations) - Product Id Vs Opportunity Type

Bivariate Plots (top 50 Correlations) - Product Id Vs Core Product Application

Bivariate Plots (top 50 Correlations) - Product Quantity Vs Decision Time Days

Bivariate Plots (top 50 Correlations) - Target Vs Geography

Bivariate Plots (top 50 Correlations) - Target Vs Core Sales Segment

Bivariate Plots (top 50 Correlations) - Geography Vs Did Convert

Bivariate Plots (top 50 Correlations) - Core Product Segment Vs Core Consumption Market

Bivariate Plots (top 50 Correlations) - Opportunity Status Vs Geography

Bivariate Plots (top 50 Correlations) - Stage Level Vs Core Product Application

Key Drivers

Target

Target - Feature Scores - Feature Correlation

Target - Feature Importances - From Model

Target - Pca Analysis

Target - Pca Analysis - Pca Projection

Target - Pca Analysis - Correlation With Dimension 2 (y)

Target - Pca Analysis - Correlation With Dimension 1 (x)

Target - Bivariate Plots

Target - Bivariate Plots - Index

Target - Bivariate Plots - Stage Level

Target - Bivariate Plots - Product $

Target - Bivariate Plots - Core Product Segment

Target - Bivariate Plots - Early Stages

Target - Bivariate Plots - Core Product Application

Target - Bivariate Plots - Transition To Stage

Target - Bivariate Plots - Did Convert

Target - Bivariate Plots - Transition Time Days

Target - Bivariate Plots - Transition From Stage Name

Target - Bivariate Plots - Opportunity Status

Target - Bivariate Plots - Decision Time Days

Target - Bivariate Plots - Core Sales Segment

Target - Bivariate Plots - Geography

Target - Bivariate Plots - Product Id

Target - Bivariate Plots - Opportunity Type

Target - Bivariate Plots - Product Quantity

Target - Bivariate Plots - Core Consumption Market